Estimation of generalized exponential distribution under dual generalized order statistics

2016 ◽  
Vol 10 ◽  
pp. 2903-2919
Author(s):  
Chansoo Kim
2015 ◽  
Vol 4 (2) ◽  
pp. 370
Author(s):  
Eldesoky Afify

<p>Estimation of a parameter of generalized exponential distribution (gexp) is obtained based on generalized order statistics. The maximum likelihood and Bayes methods are used for this purpose. Survival function and hazard rate are also computed. Estimation based on upper record values from generalized exponential distribution is obtained as a special case and compared by simulated data.</p>


2018 ◽  
Vol 11 (4) ◽  
pp. 929-936 ◽  
Author(s):  
Saman Hanif Shahbaz ◽  
Muhammad Qaiser Shahbaz

The concomitants of Dual Generalized Order Statistics for InverseExponential distribution has been studied. Specifically the distributionalproperties of r--th concomitant and joint distribution of r--th and s--thconcomitant of dual generalized order statistics have been studied whensample is available from a bivariate inverse exponential distribution.


Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 335
Author(s):  
Mohamed A. Abd Elgawad ◽  
Haroon M. Barakat ◽  
Shengwu Xiong ◽  
Salem A. Alyami

In this paper, we study the concomitants of dual generalized order statistics (and consequently generalized order statistics) when the parameters γ1,⋯,γn are assumed to be pairwise different from Huang–Kotz Farlie–Gumble–Morgenstern bivariate distribution. Some useful recurrence relations between single and product moments of concomitants are obtained. Moreover, Shannon’s entropy and the Fisher information number measures are derived. Finally, these measures are extensively studied for some well-known distributions such as exponential, Pareto and power distributions. The main motivation of the study of the concomitants of generalized order statistics (as an important practical kind to order the bivariate data) under this general framework is to enable researchers in different fields of statistics to use some of the important models contained in these generalized order statistics only under this general framework. These extended models are frequently used in the reliability theory, such as the progressive type-II censored order statistics.


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